Tag: Amazon S3

CAD on the cloud delivers the same, if not better, performance than on-premises setup. For enterprises, it will be a paradigm shift to have their CAD/CAE workload on the cloud, especially using Amazon AppStream 2.0. Learn about Infosys’ flagship Cobalt program, one of the largest service providers in engineering and design, with decades of experience helping customers leverage AWS to optimize cost and performance.

In construction, new methods of capturing site information, such as laser scanning, photogrammetry, drone photography, and continuous video monitoring have presented challenges for file storage, analysis, and archiving. Learn how the Nasuni Analytics Connector can help architecture, engineering, and construction customers gain business insight from file data, while using many of the network-attached storage they’re familiar with.

Data is the most important resource available to modern institutions. The challenge is not necessarily generating, cataloging, or storing data, but operationalizing it. Palantir Foundry is an operations platform that leverages existing data systems and analytics tooling to power smarter decision-making. Learn how Palantir HyperAuto can rapidly integrate data from ERP systems and operationalize that existing data against pressing business problems.

The zero-cost Amazon Sustainability Data Initiative (ASDI) seeks to accelerate sustainability research and innovation by minimizing the cost and time required to analyze large sustainability datasets. In this post, we’ll use Snowflake, a data cloud company, to work with two different ASDI datasets containing climate and air quality data. We’ll demonstrate how to access ASDI datasets, join them together by date, and ultimately form a merged result.

In the digital-first era, being a content platform means serving thousands of requests per second to users all over the world. Learn how Contentful delivers media files using Amazon CloudFront with Lambda@Edge, achieving low latency on every region worldwide while also running custom-code at the edge that enables security features and high availability. With Lambda@Edge, Contentful can easily ship code that runs close to the user to deliver secure assets.

Learn how Storm Reply used AWS IoT services to implement a solution that is highly scalable, easy to maintain, and optimized to satisfy custom requirements for Schenck Process Group, a global market leader in measurement and process technology. Storm Reply’s approach is to pair the edge device capabilities of AWS IoT Greengrass with the storage and processing power of AWS and pairing these tools with a custom, high-quality web application.

If you or your company is struggling to set up your ecommerce solution, or if your current ecommerce site is not resonating with customers like you would hope, you are not alone. Learn about the Adobe Commerce open source solution, how it can be deployed using a Quick Start that was developed by Shero Commerce, and how Shero can help with your Adobe Commerce system to enhance your customer’s digital shopping experience.

The restaurant industry is experiencing an unprecedented transformational change. Elevated expectations for cleanliness, health, and safety are accelerating the adoption of contactless technologies, curbside pickup options, and mobile payments. Learn how Capgemini’s Digital Cloud Platform (DCP) for Restaurants empowers the industry to reimagine digital transformation by delivering compelling customer interaction and streamlined operations while reducing costs and improving efficiency.

Large-scale database migrations are difficult, have multiple phases, and are time-consuming. Customers want a simpler way to achieve large-scale migration with little to no downtime. Learn how Futuralis helped their customer migrate more than 50,000 MySQL databases hosted on an Amazon EC2 server to Amazon Aurora relational database using AWS and native MySQL tools. The customer had MySQL version 5.5 hosted on EC2 with more than 50,000 databases with 1.5 million tables and hundreds of millions of records.

Organizations hosting customer-specific machine learning models on AWS have unique isolation and performance requirements and require a solution that provides a scalable, high-performance, and feature-rich ML platform. Learn how Amazon SageMaker Pipelines helps you to pre-process data, build, train, tune, and register ML models in SaaS applications. We’ll focus on best practices for building tenant-specific ML models with particular focus on tenant isolation and cost attribution.